AUV SLAM and experiments using a mechanical scanning forward-looking sonar

Sensors (Switzerland)

Volumn 12, Issue 7, 2012, Pages 9386-9410

  He, Bo ^a   Liang, Yan ^a   Feng, Xiao ^a   Nian, Rui ^a   Yan, Tianhong ^b   Li, Minghui ^c   Zhang, Shujing ^a  

^a OCEAN UNIVERSITY OF CHINA   (China)

^b CHINA JILIANG UNIVERSITY   (China)

^c UNIVERSITY OF STRATHCLYDE   (United Kingdom)

Author keywords

AUV; FastSLAM; Mechanical scanning imaging sonar

Indexed keywords

EID: 84864354718     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s120709386     Document Type: Article

References (36)

1. Durrant-Whyte, H.; Bailey, T. Simultaneous localization and mapping: Part 1. IEEE Robot. Autom. Mag. 2006, 13, 99-110.
2. Wilfong, G.; Josep, E. Simultaneous Localization and Mapping: A Survey; Springer-Verlag: Heidelberg, Germany, 1990; pp. 167-193.
3. Blanco, J.L.; Fernadez-Madrigal, J.A.; Gonzalez, J. A novel measure of uncertainty for mobile robot SLAM with Rao-Blackwellized Particle Filters. Int. J. Robot. Res. 2008, 21, 73-89.
4. Smith, R.; Cheeseman, P. On the representation and estimation of spatial uncertainty. Int. J. Robot. Res. 1986, 5, 56-68.
5. Smith, R.; Self, M.; Cheeseman, P. Estimating uncertain spatial relationships in robotics. Auton. Robot Veh. 1990, 8, 167-193.
6. Maybeck, P.S. Stochastic Models, Estimation, and Control; Academic Press: New York, NY, USA, 1979.
7. Guivant, J.; Nebot, E. Improved Computational and Memory Requirements of Simultaneous Localization and Map Building Algorithms. In Proceedings of the IEEE International Conference on Robotics & Automation (ICRA), Washington, DC, USA, 11-15 May 2002; pp. 2731-2736.
8. Guivant, J.; Nebot, E. Optimization of the simultaneous localization and map-building algorithm for real-time implementation. IEEE Trans. Robot. Autom. 2001, 17, 242-257.
9. Williams, S.; Dissanayake, G.; Durrant-Whyte, H. An Efficient Approach to the Simultaneous Localisation and Mapping Problem. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Washington, DC, USA, 11-15 May 2002; pp. 406-411.
10. Leonard, J.; Newman, P. Consistent, Convergent, and Constant-Time SLAM. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Acapulco, Mexico, 9-15 August 2003; pp. 1143-1150.
11. Bosse, M.; Newman, P.; Leonard, J.; Teller, S. Simultaneous localization and map building in large-scale cyclic environments using the atlas framework. Int. J. Robot. Res. 2004, 23, 1113-1139.
12. Walter, M.; Eustice, R.; Leonard, J. A provably consistent method for imposing sparsity in feature-based SLAM information filters. Springer Tracts Adv. Robot. 2008, 28, 214-234.
13. Thrun, S.; Liu, Y.; Koller, D. Simultaneous localization and mapping with sparse extended information filters: theory and initial results. Springer Tracts Adv. Robot. 2004, 7, 363-380.
14. Liu, Y.; Thrun, S. Results for Outdoor-SLAM Using Sparse Extended Information Filters. In Proceedings of the IEEE International Conference on Robotics and Automation(ICRA), Taipei, Taiwan, 14-19 September 2003; pp. 1227-1233.
15. Thrun, S.; Liu, Y.; Koller, D. Simultaneous localization and mapping with Sparse Extended Information Filters. Int. J. Robot. Res. 2004, 23, 693-716.
16. Thrun, S.; Burgard, D.; Fox, W. Probabilistic Robotics; MIT Press: Cambridge, MA, USA, 2005.
17. ArulamPalam, M.S.; Maskell, S.; Gordon, N.; Clapp, T. A tutorial on particle filters for on-line non-linear/non-Gaussian Bayesian tracking. IEEE Trans. Signal Proc. 2002, 50, 174-188.
18. Murphy, K. Bayesian map learning in dynamic environment. Adv. Neural Inf. Proc. Syst. 1999, 12, 1015-1021.
19. Doucet, A.; de Freitas, N.; Murphy, K.; Russell, S. Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. In Proceedings of the Sixteenth Conference on Uncertainty in Artificial Intelligence(UAI), Stanford, CA, USA, 30 June-3 July 2000; pp. 176-183.
20. Montemerlo, M.; Thrun, S.; Koller, D.; Wegbreit, B. FastSLAM: A Factored Solution to the Simultaneous Localization and Mapping Problem. In Proceedings of the AAAI National Conference on Artificial Intelligence, Edmonton, AB, Canada, 28 July-1 August 2002; pp. 593-598.
21. Montemerlo, M.; Thrun, S.; Koller, D.; Wegbreit, B. FastSLAM 2.0: An Improved Particle Filtering Algorithm for Simultaneous Localization and Mapping that Provably Converges. In Proceedings of the International Conference on Artificial Intelligence, Hyderabad, India, 18-20 December 2003; pp. 1153-1156.
22. Bailey, T.; Nieto, J.; Nebot, E. Consistency of the FastSLAM Algorithm. In Proceedings of the 2006 IEEE International Conference on Robotics and Automation(ICRA), Orlando, FL, USA, 15-19 May 2006; pp. 424-429.
23. Durrant-Whyte, H.; Majumder, S.; Thrun, S.; de Battista, M.; Scheding, S. A bayesian algorithm for simultaneous localisation and map building. Robot. Res. 2003, 6, 49-60.
24. Leonard, J.L.; Carpenter, R.N.; Feder, H.J.S. Stochastic mapping using forward look sonar. Robotica 2001, 19, 467-480.
25. Ruiz, I.T.; Petillot, Y.; Lane, D.M. Improved AUV Navigation Using Side-Scan Sonar. In Proceedings of OCEANS, San Diego, CA, USA, 22-26 September 2003; pp. 1261-1268.
26. He, B.; Zhang, S.J.; Li, C.; Zhang, S.J.; Liang, Y.; Tian, H.Y. Autonomous navigation for autonomous underwater vehicles based on information filters and active sensing. Sensors 2011, 11, 10598-10980.
27. Ribas, D. Abandoned Marina Dataset-Experiment performed at the Fluvia Nautic abandoned marina near St Pere Pescador (Spain). 2007. Available online: http://cres.usc.edu/radishrepository/view-one.php?name=abandoned_marina (accessed on 8 June 2012).
28. Montemerlo, M.; Thrun, S. Simultaneous Localization and Mapping with Unknown Data Association Using FastSLAM. In Proceedings of the IEEE International Conference on Robotics and Automation, Taipei, Taiwan, 14-19 September 2003; pp. 1985-1991.
29. Zhou, W.; Zhao, C.X.; Haofeng, Z. Dynamic joint nearest neighbor algorithm. Acta Electr. Sinica 2010, 38, 359-364.
30. Kwak, N.; Kim, G.W.; Lee, B.H. A new compensation technique based on analysis of resampling process in fastslam. Robotica 2008, 26, 205-217.
31. Kwak, N.; Yokoi, K.; Lee, B.H. Analysis of rank-based resampling based on particle diversity in the rao-blackwellized particle filter for simultaneous localization and mapping. Adv. Robot. 2010, 24, 585-604.
32. Zhang, L.; Jiang, X.R.; Chen, Y.W. Algorithm for mobile robots' simultaneous localization and mapping in unknown environments. Control Dec. 2010, 25, 515-520.
33. Schon, T.; Gustafsson, F.; Nordlund, P. Marginalized particle filters for mixed linear/nonlinear state-space models. IEEE Trans. Signal Proc. 2005, 53, 2279-2289.
34. He, B.; Zhang, S.J.; Yan, T.H.; Zhang, T.; Liang, Y.; Zhang, H.J. A novel combined SLAM based on RBPF-SLAM and EIF-SLAM for mobile system sensing in a large scale environment. Sensors 2011, 11, 10197-10219.
35. Forouher et. al. Sonar-based FastSLAM in an Underwater Environment Using Walls as Features. In Proceedings of the 15th International Conference on Advanced Robotics, Tallinn, Estonia, 20-23 June 2011; pp. 588-593.
36. Bailey, T. FastSLAM2.0 Simulator. Available online: http://www-personal.acfr.usyd.edu.au/tbailey/(accessed on 8 June 2012).